Instructions to use abenzerps/ZDTaichu5.0-9B-DSpark-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use abenzerps/ZDTaichu5.0-9B-DSpark-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

Use Docker

docker model run hf.co/abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use abenzerps/ZDTaichu5.0-9B-DSpark-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "abenzerps/ZDTaichu5.0-9B-DSpark-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "abenzerps/ZDTaichu5.0-9B-DSpark-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

Ollama
How to use abenzerps/ZDTaichu5.0-9B-DSpark-GGUF with Ollama:
```
ollama run hf.co/abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M
```
Unsloth Desktop

How to use abenzerps/ZDTaichu5.0-9B-DSpark-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use abenzerps/ZDTaichu5.0-9B-DSpark-GGUF with Docker Model Runner:
```
docker model run hf.co/abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M
```

Lemonade

How to use abenzerps/ZDTaichu5.0-9B-DSpark-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.ZDTaichu5.0-9B-DSpark-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use abenzerps/ZDTaichu5.0-9B-DSpark-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use abenzerps/ZDTaichu5.0-9B-DSpark-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "abenzerps/ZDTaichu5.0-9B-DSpark-GGUF:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

ZDTaichu5.0-9B-DSpark-GGUF / README.md

abenzerps

Initial commit

258557e 27 days ago

preview code

Raw History Blame Contribute Delete

5.49 kB

	---
	license: apache-2.0
	language:
	- en
	- zh
	base_model:
	- TaichuAI/ZDTaichu5.0-9B
	- TaichuAI/ZDTaichu5.0-9B-DSpark
	base_model_relation: quantized
	pipeline_tag: text-generation
	library_name: gguf
	tags:
	- gguf
	- llama.cpp
	- speculative-decoding
	- draft-model
	- dspark
	- dflash
	- zdtaichu5_0
	- qwen3.5
	- agent
	---

	[![🤗 Model Requests](https://img.shields.io/badge/%F0%9F%A4%97_Model_Requests-Submit_Here-f59e0b?style=for-the-badge&labelColor=1f2937)](https://abenzerps.com/request-a-model/)

	# ZDTaichu5.0-9B DSpark GGUF

	GGUF files for [ZDTaichu5.0-9B-DSpark](https://huggingface.co/TaichuAI/ZDTaichu5.0-9B-DSpark), the official semi-autoregressive speculative decoding draft model developed by the Zi Dong Tai Chu team to accelerate [ZDTaichu5.0-9B](https://huggingface.co/TaichuAI/ZDTaichu5.0-9B).

	> [!NOTE]
	> This is a speculative decoding draft model (D-Spark / DFlash), not a standalone general model. It must be paired with the primary [ZDTaichu5.0-9B GGUF](https://huggingface.co/abenzerps/ZDTaichu5.0-9B-GGUF) model during inference to increase generation speeds by up to 60–85%.

	## Benchmarks

	![ZDTaichu5.0-9B benchmark results](assets/taichu-vs-closed-models.png)

	Benchmark results reported by TaichuAI for the original ZDTaichu5.0-9B foundation model. These figures are not measurements of this GGUF conversion.

	## GGUF files

	\| Quantization \| DSpark Draft File \| Draft Size \| Paired Base Model File \|
	\| :--- \| :--- \| ---: \| :--- \|
	\| BF16 \| [ZDTaichu5.0-9B-DSpark-BF16.gguf](https://huggingface.co/abenzerps/ZDTaichu5.0-9B-DSpark-GGUF/blob/main/ZDTaichu5.0-9B-DSpark-BF16.gguf) \| 4.40 GB \| [TaichuAI/ZDTaichu5.0-9B](https://huggingface.co/TaichuAI/ZDTaichu5.0-9B) (Original Weights) \|
	\| Q8_0 \| [ZDTaichu5.0-9B-DSpark-Q8_0.gguf](https://huggingface.co/abenzerps/ZDTaichu5.0-9B-DSpark-GGUF/blob/main/ZDTaichu5.0-9B-DSpark-Q8_0.gguf) \| 2.34 GB \| [ZDTaichu5.0-9B-Q8_0.gguf](https://huggingface.co/abenzerps/ZDTaichu5.0-9B-GGUF/blob/main/ZDTaichu5.0-9B-Q8_0.gguf) (9.53 GB) \|
	\| Q6_K \| [ZDTaichu5.0-9B-DSpark-Q6_K.gguf](https://huggingface.co/abenzerps/ZDTaichu5.0-9B-DSpark-GGUF/blob/main/ZDTaichu5.0-9B-DSpark-Q6_K.gguf) \| 1.81 GB \| [ZDTaichu5.0-9B-Q6_K.gguf](https://huggingface.co/abenzerps/ZDTaichu5.0-9B-GGUF/blob/main/ZDTaichu5.0-9B-Q6_K.gguf) (7.36 GB) \|
	\| Q5_K_M \| [ZDTaichu5.0-9B-DSpark-Q5_K_M.gguf](https://huggingface.co/abenzerps/ZDTaichu5.0-9B-DSpark-GGUF/blob/main/ZDTaichu5.0-9B-DSpark-Q5_K_M.gguf) \| 1.67 GB \| [ZDTaichu5.0-9B-Q5_K_M.gguf](https://huggingface.co/abenzerps/ZDTaichu5.0-9B-GGUF/blob/main/ZDTaichu5.0-9B-Q5_K_M.gguf) (6.47 GB) \|
	\| Q4_K_M \| [ZDTaichu5.0-9B-DSpark-Q4_K_M.gguf](https://huggingface.co/abenzerps/ZDTaichu5.0-9B-DSpark-GGUF/blob/main/ZDTaichu5.0-9B-DSpark-Q4_K_M.gguf) \| 1.53 GB \| [ZDTaichu5.0-9B-Q4_K_M.gguf](https://huggingface.co/abenzerps/ZDTaichu5.0-9B-GGUF/blob/main/ZDTaichu5.0-9B-Q4_K_M.gguf) (5.63 GB) \|
	\| Q4_0 \| [ZDTaichu5.0-9B-DSpark-Q4_0.gguf](https://huggingface.co/abenzerps/ZDTaichu5.0-9B-DSpark-GGUF/blob/main/ZDTaichu5.0-9B-DSpark-Q4_0.gguf) \| 1.51 GB \| [ZDTaichu5.0-9B-Q4_0.gguf](https://huggingface.co/abenzerps/ZDTaichu5.0-9B-GGUF/blob/main/ZDTaichu5.0-9B-Q4_0.gguf) (5.31 GB) \|

	### Draft model architecture

	- Framework: DSpark (semi-autoregressive DFlash backbone + chained Markov head).
	- Target Layers: Extracts auxiliary hidden states from target layers `[1, 8, 15, 22, 29]`.
	- Block Size: 8 tokens drafted per forward pass (`dflash.block_size = 8`).
	- Target Model: [ZDTaichu5.0-9B GGUF](https://huggingface.co/abenzerps/ZDTaichu5.0-9B-GGUF).

	## Usage

	Use this draft model alongside the primary target model [abenzerps/ZDTaichu5.0-9B-GGUF](https://huggingface.co/abenzerps/ZDTaichu5.0-9B-GGUF) with `llama.cpp` (`llama-cli` or `llama-server`):

	### Text generation with Speculative Decoding (`llama-cli`)

	```bash
	llama-cli \
	-m ZDTaichu5.0-9B-Q4_K_M.gguf \
	-md ZDTaichu5.0-9B-DSpark-Q4_K_M.gguf \
	--spec-type draft-dspark \
	--spec-draft-n-max 8 \
	-c 8192 --jinja \
	--temp 0.7 --top-p 0.95 \
	-p "Explain why reproducible builds matter."
	```

	### Multimodal vision understanding with Speculative Decoding (`llama-cli`)

	```bash
	llama-cli \
	-m ZDTaichu5.0-9B-Q4_K_M.gguf \
	-md ZDTaichu5.0-9B-DSpark-Q4_K_M.gguf \
	--mmproj mmproj-ZDTaichu5.0-9B-BF16.gguf \
	--spec-type draft-dspark \
	--spec-draft-n-max 8 \
	--image path/to/image.jpg \
	-p "Describe what is shown in this image in detail."
	```

	### OpenAI-compatible server with Speculative Decoding (`llama-server`)

	```bash
	llama-server \
	-m ZDTaichu5.0-9B-Q4_K_M.gguf \
	-md ZDTaichu5.0-9B-DSpark-Q4_K_M.gguf \
	--mmproj mmproj-ZDTaichu5.0-9B-BF16.gguf \
	--spec-type draft-dspark \
	--spec-draft-n-max 8 \
	-c 8192 --jinja -fa on --host 0.0.0.0 --port 8080
	```

	Increase context `-c` up to 131,072 tokens (128K) when sufficient memory is available.

	## Source and build

	- Source draft model: [TaichuAI/ZDTaichu5.0-9B-DSpark](https://huggingface.co/TaichuAI/ZDTaichu5.0-9B-DSpark)
	- Target base model: [TaichuAI/ZDTaichu5.0-9B](https://huggingface.co/TaichuAI/ZDTaichu5.0-9B)
	- Conversion: [ggml-org/llama.cpp](https://github.com/ggml-org/llama.cpp) commit [7ceed8737fdb4eb09b4760e77bd12d38012de5a8](https://github.com/ggml-org/llama.cpp/commit/7ceed8737fdb4eb09b4760e77bd12d38012de5a8)
	- License: [Apache-2.0](https://www.apache.org/licenses/LICENSE-2.0)
	- Checksums: [SHA256SUMS.txt](SHA256SUMS.txt)